This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management m...This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management measures.Through practical observation and logical analysis,this article elaborates on the management connotations of large-scale machinery and equipment in highway construction,affirming its management value from different perspectives.On this basis,it carefully analyzes the problems existing in the management of large-scale machinery and equipment,providing a detailed interpretation of issues such as the weak foundation of the equipment management system and the disconnection between equipment selection and configuration from reality.Combining the manifestations of related problems,this article proposes strategies such as strengthening the institutional foundation of equipment management,selecting and configuring equipment based on actual conditions,aiming to provide references for large-scale machinery and equipment management to relevant enterprises.展开更多
This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is...This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is placed on data acquisition and processing methods using total stations and automated monitoring systems.Through a comprehensive analysis of lateral,longitudinal,and vertical displacement data from 26 subgrade monitoring points,catenary columns,and track sections,this research evaluates how construction activities influence railway structures.The results show that displacement variations in the subgrades,catenary columns,and tracks remained within the established alert thresholds,exhibiting stable deformation trends and indicating that any adverse environmental impact was effectively contained.Furthermore,this paper proposes an early warning mechanism based on an automated monitoring system,which can promptly detect abnormal deformations and initiate emergency response procedures,thereby ensuring the safe operation of the railway.The integration of big data analysis and deformation prediction models offers a practical foundation for future safety management in railway construction.展开更多
The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D desi...The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.展开更多
[Objective] The behavior of eating, drinking, defecating and peeing of 1 500 pigs in a large-scale microbial fermentation bed-equipped piggery was observed. We hoped to find some simple indicators that could reflect t...[Objective] The behavior of eating, drinking, defecating and peeing of 1 500 pigs in a large-scale microbial fermentation bed-equipped piggery was observed. We hoped to find some simple indicators that could reflect the health status of swinery and to provide experience for the swinery performance management in large-scale microbial fermentation bed-equipped piggery. [Method] The body weight （BW）, daily BW gain, feed intake and other indicators of different-day-old pigs were recorded in details. Based on the recorded data, the models between BW, BW gain, average daily feed intake and feed/gain ratio and growth days （d） were established. In addition, the incidences of pox-like macula （dermatitis）, diarrhea （gastrointestinal disease）, cough （respiratory disease）, stiff pig （malnutrition）, conjunctivitis （eye disease） and foot inflection （trauma） among fattening pigs were also investigated. [Result] The BW range, average BW, daily BW gain, breeding days, daily feed intake range, average daily feed intake, staged feed intake, accumulated feed intake, feed/gain ratio and accumulated feed/gain ratio of different-day-old pigs were studied, respectively. Four dynamic models were established for the growth of pigs： （1） the BW （y）-age （x） mod- el： y=0.758 9x-19.883 （3=0.993 7）; （2） the BW gain （y）-age （x） model： y=1.039 5x05051 （F=0.885 4）; （3） the average daily feed intake （y）-age （x） model： y=0.023 5x-0.334 3 （F=0.991 7）; （4） the feed/gain ratio （y）-age （x） model： y=0.022x＋0.427 8 （P=0.988 5）. Based on these models, the corresponding theoretical growth value of pigs at different growth stage could be predicted. The main diseases occurred among the swinery in the large-scale microbial fermentation bed piggery included pox-like macula （dermatitis）, diarrhea （gastrointestinal disease）, cough （respiratory disease）, stiff pig （mal- nutrition）, conjunctivitis （eye disease） and foot inflection （trauma）. The deadly infec- tious diseases had been not found among the pigs. [Conclusion] When the actual BW, BW gain, average daily feed intake and feed/gain ratio were all lower than the theoretical values predicted by the models, the management should be enhanced. The average daily feed intake of 60 to 65-day-old pigs was lower than the theoretic value, indicating that the pigs could not adapt nicely to the fermentation bed at the very early stage. When the pigs grew up to 70 to 75 d old, the average daily feed intake was higher than the theoretical value, indicating that the pigs had adapted to the fermentation bed. In particularly, average daily feed intake of 75-day-old pigs was higher than the theoretical value by 21%. It was suggested the fermentation bed was conducive to the growth of pigs. Considering the occurrence of diseases among pigs, the overall incidence was relatively low. The incidence of each disease was all lower than 10% with little difficulty in treating. If the management of mattress was strength- ened, such as paying attention to feeding and keeping water clean, many diseases could heal by themselves.展开更多
Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynam...Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.展开更多
Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fund...Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.展开更多
Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bot...Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bottleneck,severely affecting device stability and long-term operational performance.Herein,we present a multifunctional strategy by incorporating highly thermally conductive Ti_(3)C_(2)T_(X) MXene nanosheets into the perovskite layer to simultaneously enhance thermal management and optoelectronic properties.The Ti_(3)C_(2)T_(X) nanosheets,embedded at perovskite grain boundaries,construct efficient thermal conduction pathways,significantly improving the thermal conductivity and diffusivity of the film.This leads to a notable reduction in the device’s steady-state operating temperature from 42.96 to 39.97 under 100 mW cm^(−2) illumination,thereby alleviating heat-induced performance degradation.Beyond thermal regulation,Ti_(3)C_(2)T_(X),with high conductivity and negatively charged surface terminations,also serves as an effective defect passivation agent,reducing trap-assisted recombination,while simultaneously facilitating charge extraction and transport by optimizing interfacial energy alignment.As a result,the Ti_(3)C_(2)T_(X)-modified PSC achieve a champion PCE of 25.13%and exhibit outstanding thermal stability,retaining 80%of the initial PCE after 500 h of thermal aging at 85 and 30±5%relative humidity.(In contrast,control PSC retain only 58%after 200 h.)Moreover,under continuous maximum power point tracking in N2 atmosphere,Ti_(3)C_(2)T_(X)-modified PSC retained 70%of the initial PCE after 500 h,whereas the control PSC drop sharply to 20%.These findings highlight the synergistic role of Ti_(3)C_(2)T_(X) in thermal management and optoelectronic performance,paving the way for the development of high-efficiency and heat-resistant perovskite photovoltaics.展开更多
As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-govern...As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to miti...Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to mitigate the freshwater,energy and food crises.However,the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather.This study proposes an integrated water/electricity cogeneration-cultivation system with superior thermal management.The energy storage evaporator,consisting of energy storage microcapsules/hydrogel composites,is optimally designed for sustainable desalination,achieving an evaporation rate of around 1.91 kg m^(-2)h^(-1).In the dark,heat released from the phase-change layer supported an evaporation rate of around 0.54kg m^(-2)h^(-1).Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination,enabling the long-running WEC system to achieve a power output of~0.3 W m^(-2),which was almost three times higher than that of conventional seawater/surface water mixing.Additionally,an integrated crop irrigation platform utilized system drainage for real-time,on-demand wheat cultivation without secondary contaminants,facilitating seamless WEF integration.This work presents a novel approach to all-day solar water production,electricity generation and crop irrigation,offering a solution and blueprint for the sustainable development of WEF.展开更多
Lassa fever(LF)is an acute viral hemorrhagic illness caused by the Lassa virus(LASV),an enveloped,spherical virus belonging to the Arenaviridae family.LASV possess a single-stranded RNA genome of negative polarity and...Lassa fever(LF)is an acute viral hemorrhagic illness caused by the Lassa virus(LASV),an enveloped,spherical virus belonging to the Arenaviridae family.LASV possess a single-stranded RNA genome of negative polarity and exhibits high genetic diversity,corresponding to the geographical distribution of its seven principal distinct clades across West Africa[1].LASV was first isolated in 1969 from an American missionary nurse stationed in the rural town of Lassa,Borno State,Nigeria,following her return from a brief vacation in the United States[2].展开更多
The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to ...The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerou...As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.展开更多
Due to the new situation of continuous expansion of scientific and technological resources in universities and the urgent demand for hardware resources for science and technology innovation it is imperative to strengt...Due to the new situation of continuous expansion of scientific and technological resources in universities and the urgent demand for hardware resources for science and technology innovation it is imperative to strengthen the construction of large-scale instrument service platforms and open access management.It is not only the requirements for the development of instrument service platforms,but also the resources for science and technology of society.In the present paper,we first summarized the current equipment management,open access and major experience,then raised the problems in the construction and management process on the basis of the large instrument platform construction and open access management regulations,and finally proposed countermeasures for these problems:increasing funding input,streamlining the management system,improving the performance evaluation mechanism,and strengthening the management and operation team construction,etc.Collectively,this paper provided reference and enlightenment for the construction and open access management of similar large-scale instrument platforms.展开更多
Temperature regulating fibers(TRF_(s)) with high enthalpy and high form stability are the key factors for thermal management. However, the enthalpies of most TRFsare not high, and the preparation methods are still at ...Temperature regulating fibers(TRF_(s)) with high enthalpy and high form stability are the key factors for thermal management. However, the enthalpies of most TRFsare not high, and the preparation methods are still at the laboratory scale. It remains a great challenge to use industrial spinning equipment to achieve continuous processing of TRF_(s) with excellent thermal and mechanical properties. Here, polyamide 6(PA6) based TRF_(s) with a sheath-core structure were prepared by bicomponent melt-spinning. The sheath-core TRF(TRF_(sc)) are composed of PA6 as sheath and functional PA6 as core, which are filled with the shape stable phase change materials(ssPCM),dendritic silica@polyethylene glycol(SiO_(2)@PEG). With the aid of the sheath structure, the filling content of SiO_(2)@PEG can reach 30 %, so that the enthalpy of the TRF_(s) can be as high as 21.3 J/g. The ultra-high enthalpy guarantees the temperature regulation ability during the alternating process of cooling and heating. In hot environment, the temperature regulation time is 6.59 min, and the temperature difference is 12.93℃. In addition, the mechanical strength of the prepared TRF_(sc) reaches 2.26 cN/dtex, which can fully meet its application in the field of thermal management textiles and devices to manage the temperature regulation of the human body or precision equipment, etc.展开更多
Signal transmission control protocol sources with the objective of managing queue utilization and delay is actually a feedback control problem in active queue management (AQM) core routers. This paper extends AQM cont...Signal transmission control protocol sources with the objective of managing queue utilization and delay is actually a feedback control problem in active queue management (AQM) core routers. This paper extends AQM control design for single network systems to large-scale wired network systems with time delays at each communication channel. A system model consisted of several local networks is first constructed. The stability condition guaranteeing overall stability is subsequently derived using Lyapunov stability theory. The results developed have been successfully verified on a network simulator.展开更多
文摘This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management measures.Through practical observation and logical analysis,this article elaborates on the management connotations of large-scale machinery and equipment in highway construction,affirming its management value from different perspectives.On this basis,it carefully analyzes the problems existing in the management of large-scale machinery and equipment,providing a detailed interpretation of issues such as the weak foundation of the equipment management system and the disconnection between equipment selection and configuration from reality.Combining the manifestations of related problems,this article proposes strategies such as strengthening the institutional foundation of equipment management,selecting and configuring equipment based on actual conditions,aiming to provide references for large-scale machinery and equipment management to relevant enterprises.
文摘This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is placed on data acquisition and processing methods using total stations and automated monitoring systems.Through a comprehensive analysis of lateral,longitudinal,and vertical displacement data from 26 subgrade monitoring points,catenary columns,and track sections,this research evaluates how construction activities influence railway structures.The results show that displacement variations in the subgrades,catenary columns,and tracks remained within the established alert thresholds,exhibiting stable deformation trends and indicating that any adverse environmental impact was effectively contained.Furthermore,this paper proposes an early warning mechanism based on an automated monitoring system,which can promptly detect abnormal deformations and initiate emergency response procedures,thereby ensuring the safe operation of the railway.The integration of big data analysis and deformation prediction models offers a practical foundation for future safety management in railway construction.
文摘The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.
基金Supported by International Science and Technology Cooperation Project of China(2012DFA31120)Special Fund for Agro-scientific Research in the Public Interest(201303094)National Key Technology Research and Development Program(2012BAD14B15)~~
文摘[Objective] The behavior of eating, drinking, defecating and peeing of 1 500 pigs in a large-scale microbial fermentation bed-equipped piggery was observed. We hoped to find some simple indicators that could reflect the health status of swinery and to provide experience for the swinery performance management in large-scale microbial fermentation bed-equipped piggery. [Method] The body weight （BW）, daily BW gain, feed intake and other indicators of different-day-old pigs were recorded in details. Based on the recorded data, the models between BW, BW gain, average daily feed intake and feed/gain ratio and growth days （d） were established. In addition, the incidences of pox-like macula （dermatitis）, diarrhea （gastrointestinal disease）, cough （respiratory disease）, stiff pig （malnutrition）, conjunctivitis （eye disease） and foot inflection （trauma） among fattening pigs were also investigated. [Result] The BW range, average BW, daily BW gain, breeding days, daily feed intake range, average daily feed intake, staged feed intake, accumulated feed intake, feed/gain ratio and accumulated feed/gain ratio of different-day-old pigs were studied, respectively. Four dynamic models were established for the growth of pigs： （1） the BW （y）-age （x） mod- el： y=0.758 9x-19.883 （3=0.993 7）; （2） the BW gain （y）-age （x） model： y=1.039 5x05051 （F=0.885 4）; （3） the average daily feed intake （y）-age （x） model： y=0.023 5x-0.334 3 （F=0.991 7）; （4） the feed/gain ratio （y）-age （x） model： y=0.022x＋0.427 8 （P=0.988 5）. Based on these models, the corresponding theoretical growth value of pigs at different growth stage could be predicted. The main diseases occurred among the swinery in the large-scale microbial fermentation bed piggery included pox-like macula （dermatitis）, diarrhea （gastrointestinal disease）, cough （respiratory disease）, stiff pig （mal- nutrition）, conjunctivitis （eye disease） and foot inflection （trauma）. The deadly infec- tious diseases had been not found among the pigs. [Conclusion] When the actual BW, BW gain, average daily feed intake and feed/gain ratio were all lower than the theoretical values predicted by the models, the management should be enhanced. The average daily feed intake of 60 to 65-day-old pigs was lower than the theoretic value, indicating that the pigs could not adapt nicely to the fermentation bed at the very early stage. When the pigs grew up to 70 to 75 d old, the average daily feed intake was higher than the theoretical value, indicating that the pigs had adapted to the fermentation bed. In particularly, average daily feed intake of 75-day-old pigs was higher than the theoretical value by 21%. It was suggested the fermentation bed was conducive to the growth of pigs. Considering the occurrence of diseases among pigs, the overall incidence was relatively low. The incidence of each disease was all lower than 10% with little difficulty in treating. If the management of mattress was strength- ened, such as paying attention to feeding and keeping water clean, many diseases could heal by themselves.
基金Supported by the National Natural Science Foundation of China(Nos.52293472,22473096 and 22471164)。
文摘Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.
基金supported by National Natural Science Foundation of China(32494793).
文摘Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.
基金the National Natural Science Foundation of China(Nos.62374029,22175029,62474033,and W2433038)the Young Elite Scientists Sponsorship Program by CAST(No.YESS20220550)+2 种基金the Sichuan Science and Technology Program(No.2024NSFSC0250)the Natural Science Foundation of Shenzhen Innovation Committee(JCYJ20210324135614040)the Fundamental Research Funds for the Central Universities of China(No.ZYGX2022J032).
文摘Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bottleneck,severely affecting device stability and long-term operational performance.Herein,we present a multifunctional strategy by incorporating highly thermally conductive Ti_(3)C_(2)T_(X) MXene nanosheets into the perovskite layer to simultaneously enhance thermal management and optoelectronic properties.The Ti_(3)C_(2)T_(X) nanosheets,embedded at perovskite grain boundaries,construct efficient thermal conduction pathways,significantly improving the thermal conductivity and diffusivity of the film.This leads to a notable reduction in the device’s steady-state operating temperature from 42.96 to 39.97 under 100 mW cm^(−2) illumination,thereby alleviating heat-induced performance degradation.Beyond thermal regulation,Ti_(3)C_(2)T_(X),with high conductivity and negatively charged surface terminations,also serves as an effective defect passivation agent,reducing trap-assisted recombination,while simultaneously facilitating charge extraction and transport by optimizing interfacial energy alignment.As a result,the Ti_(3)C_(2)T_(X)-modified PSC achieve a champion PCE of 25.13%and exhibit outstanding thermal stability,retaining 80%of the initial PCE after 500 h of thermal aging at 85 and 30±5%relative humidity.(In contrast,control PSC retain only 58%after 200 h.)Moreover,under continuous maximum power point tracking in N2 atmosphere,Ti_(3)C_(2)T_(X)-modified PSC retained 70%of the initial PCE after 500 h,whereas the control PSC drop sharply to 20%.These findings highlight the synergistic role of Ti_(3)C_(2)T_(X) in thermal management and optoelectronic performance,paving the way for the development of high-efficiency and heat-resistant perovskite photovoltaics.
基金supported by the National Natural Science Foundation of China(W2412135)the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
文摘As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
基金supported by the National Natural Science Foundation of China(No.52070057)China Postdoctoral Science Foundation(No.2023M730855)Heilongjiang Postdoctoral Fund(No.LBH-Z22183)for financial support。
文摘Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to mitigate the freshwater,energy and food crises.However,the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather.This study proposes an integrated water/electricity cogeneration-cultivation system with superior thermal management.The energy storage evaporator,consisting of energy storage microcapsules/hydrogel composites,is optimally designed for sustainable desalination,achieving an evaporation rate of around 1.91 kg m^(-2)h^(-1).In the dark,heat released from the phase-change layer supported an evaporation rate of around 0.54kg m^(-2)h^(-1).Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination,enabling the long-running WEC system to achieve a power output of~0.3 W m^(-2),which was almost three times higher than that of conventional seawater/surface water mixing.Additionally,an integrated crop irrigation platform utilized system drainage for real-time,on-demand wheat cultivation without secondary contaminants,facilitating seamless WEF integration.This work presents a novel approach to all-day solar water production,electricity generation and crop irrigation,offering a solution and blueprint for the sustainable development of WEF.
文摘Lassa fever(LF)is an acute viral hemorrhagic illness caused by the Lassa virus(LASV),an enveloped,spherical virus belonging to the Arenaviridae family.LASV possess a single-stranded RNA genome of negative polarity and exhibits high genetic diversity,corresponding to the geographical distribution of its seven principal distinct clades across West Africa[1].LASV was first isolated in 1969 from an American missionary nurse stationed in the rural town of Lassa,Borno State,Nigeria,following her return from a brief vacation in the United States[2].
文摘The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金This work was supported by National Key R&D Program of China under Grant 2018YFB1800802in part by the National Natural Science Foundation of China under Grant No.61771488,No.61631020 and No.61827801+1 种基金in part by State Key Laboratory of Air Traffic Management System and Technology under Grant No.SKLATM201808in part by Postgraduate Research and Practice Innovation Program of Jiangsu Province under No.KYCX190188.
文摘As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.
文摘Due to the new situation of continuous expansion of scientific and technological resources in universities and the urgent demand for hardware resources for science and technology innovation it is imperative to strengthen the construction of large-scale instrument service platforms and open access management.It is not only the requirements for the development of instrument service platforms,but also the resources for science and technology of society.In the present paper,we first summarized the current equipment management,open access and major experience,then raised the problems in the construction and management process on the basis of the large instrument platform construction and open access management regulations,and finally proposed countermeasures for these problems:increasing funding input,streamlining the management system,improving the performance evaluation mechanism,and strengthening the management and operation team construction,etc.Collectively,this paper provided reference and enlightenment for the construction and open access management of similar large-scale instrument platforms.
基金financially supported by the National Natural Science Foundation of China (52073047)the Science and Technology Commission of Shanghai Municipality (20JC1414900)+1 种基金the Program of Shanghai Technology Research Leader (20XD1433700)the INTERNATIONAL COOPERATION Fund of the Science and Technology Commission of Shanghai Municipality (20520740800)。
文摘Temperature regulating fibers(TRF_(s)) with high enthalpy and high form stability are the key factors for thermal management. However, the enthalpies of most TRFsare not high, and the preparation methods are still at the laboratory scale. It remains a great challenge to use industrial spinning equipment to achieve continuous processing of TRF_(s) with excellent thermal and mechanical properties. Here, polyamide 6(PA6) based TRF_(s) with a sheath-core structure were prepared by bicomponent melt-spinning. The sheath-core TRF(TRF_(sc)) are composed of PA6 as sheath and functional PA6 as core, which are filled with the shape stable phase change materials(ssPCM),dendritic silica@polyethylene glycol(SiO_(2)@PEG). With the aid of the sheath structure, the filling content of SiO_(2)@PEG can reach 30 %, so that the enthalpy of the TRF_(s) can be as high as 21.3 J/g. The ultra-high enthalpy guarantees the temperature regulation ability during the alternating process of cooling and heating. In hot environment, the temperature regulation time is 6.59 min, and the temperature difference is 12.93℃. In addition, the mechanical strength of the prepared TRF_(sc) reaches 2.26 cN/dtex, which can fully meet its application in the field of thermal management textiles and devices to manage the temperature regulation of the human body or precision equipment, etc.
文摘Signal transmission control protocol sources with the objective of managing queue utilization and delay is actually a feedback control problem in active queue management (AQM) core routers. This paper extends AQM control design for single network systems to large-scale wired network systems with time delays at each communication channel. A system model consisted of several local networks is first constructed. The stability condition guaranteeing overall stability is subsequently derived using Lyapunov stability theory. The results developed have been successfully verified on a network simulator.
